Perioperative management of apixaban in patients with advanced CKD undergoing a planned invasive procedure
Bibliographic record
Abstract
Oral anticoagulation therapy is used for both the prevention of stroke in atrial fibrillation (AF) and the treatment of venous thromboembolism (VTE).AF and VTE are both common among patients with chronic kidney disease (CKD).1,2 Approximately 15% to 20% of patients on dialysis have AF. 3 CKD is consistently identified as a risk factor for bleeding, including anticoagulation-associated bleeding.4 As a result, the prevention of AF/VTE-related morbidity in patients with CKD is difficult.There is growing interest in using apixaban in patients with kidney dysfunction due to its convenience and low dependence on renal elimination.Limited pharmacokinetic data have shown that patients with advanced CKD experience modest increases in apixaban area under the curve (AUC) plasma concentration-time values compared with patients with normal kidney function after a single dose.5 Dialysis has little effect on apixaban levels.6 Up to 15% to 20% of patients on anticoagulation therapy require perioperative interruption of their therapy every year.7 Interruption of apixaban in patients with advanced CKD can be challenging due to altered pharmacokinetics and delayed clearance.8 There is no data to guide clinicians facing this situation.The perioperative management of direct oral anticoagulants (DOACs) in patients with advanced CKD was identified as an important area for future research by the American College of Chest Physicians.7 We conducted a single-center, retrospective cohort study of consecutive apixaban-treated patients with advanced CKD who underwent a planned invasive procedure between June 2019 and March 2023, with the goal of describing the perioperative management of apixaban in this population and to determine the postoperative risks of major bleeding (MB), thromboembolism, and death.The study was approved by the Ottawa Health Science Network Research Ethics Board and was conducted according to the Declaration of Helsinki.Patients were included if they were 1) anticoagulated with apixaban for any indication and at any dose, and 2) had advanced CKD (CrCl ≤ 30 mL/min based on the Cockcroft-Gault formula) or were undergoing dialysis for ≥3 months before the perioperative anticoagulation encounter.Patients with acute kidney injury were excluded.9 A procedure was defined as "planned" when occurring ≥72 hours from the decision to proceed with an invasive intervention.Perioperative management of apixaban was at the discretion of the treating physician.Procedural bleed risk stratification was retrospectively assigned according to binary risk strata (low/moderate-vs high-bleed-risk), as recommended by the International Society on Thrombosis and Haemostasis (ISTH).10 We recorded data on demographics, apixaban indication/dosing, renal function, procedure details, and perioperative management.Adjudicated clinical outcomes (G.H. and J.R.S.) included the 30-day postoperative risks of arterial thromboembolism (ATE), VTE, MB, clinically relevant non-major bleeding (CRNMB) and all-cause mortality.Surgical MB and CRNMB were defined using ISTH criteria [11][12][13] ; thrombotic outcome definitions are outlined in supplemental Table 1.Continuous variables are summarized using median and interquartile
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".